22 - Practical ethics of AI, machine learning, and data science

09/06/20 • 29 min

What can you do about about the ethics of AI, Machine Learning, and other data science solutions in your daily work. Why it is important to think about implications first, not technologies. The four principles we use to address ethical challenges. Some practical ethic codes for data scientists.
BTW, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months. Find out more here.

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21 - How to avoid these 9 mistakes in data science team communication

Why data science team communication is so difficult. Analytics Translator is not the solution. Role of PM in a data-intensive solution team. Why you shouldn't rely on everyone's notes. What to do when you receive a long text. When to put things in writing and when not to. Handling difficult conversations.
BTW, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months. Find out more here.

Next Episode

23 - AutoML in plain English

Unless you have been living in a cave in the past 2 years, you have heard of AutoML. And depending on where you have heard it from, it can be the best thing ever happened to data science, the evil invention that will put thousands of data scientists out of their jobs, or anything in between. In this episode, we talk about the state of the art AutoML, what is hype versus what is reality, how to think about it practically, and how you can get started with AutoML in your team.

BTW, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months. Find out more here.